Keda Liang, Tengfei Liu, Zhe Chang, Meng Zhang, ZhiXin Li, Songsong Huang, Jing Wang
{"title":"基于最小二乘法和支持向量机的海洋内孤立波传播速度反演模型研究","authors":"Keda Liang, Tengfei Liu, Zhe Chang, Meng Zhang, ZhiXin Li, Songsong Huang, Jing Wang","doi":"10.7498/aps.72.20221633","DOIUrl":null,"url":null,"abstract":"The propagation speed is one of the important parameters of the internal solitary waves(ISWs). How to obtain the ISWs speed through optical remote sensing images accurately and quickly is an important problem to be solved. In this paper, we simulate ISWs optical remote sensing imaging and obtain an experimental database and build the ISWs speed inversion models based on a single-scene optical remote sensing image by using the least squares method and the support vector machine. The accuracy of the ISW speed inversion models were tested by using MODIS Image and GF-4 image data of the South China Sea. The study results show that: The least squares ISW speed inversion model can give the regression equation, which is more intuitive and has less accuracy in the water depth range from 300 meters to 399 meters, while the support vector machine ISW speed inversion model has high accuracy in the water depth range from 400 meters to 1200 meters and from 83 meters to 299 meters. Therefore, the two kinds of ISW speed inversion models have different advantages, and can be applied to the inversion of the ISW speed in the real ocean.","PeriodicalId":6995,"journal":{"name":"物理学报","volume":"99 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on inversion models of internal solitary wave propagation speed in ocean based on least square method and support vector machine\",\"authors\":\"Keda Liang, Tengfei Liu, Zhe Chang, Meng Zhang, ZhiXin Li, Songsong Huang, Jing Wang\",\"doi\":\"10.7498/aps.72.20221633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The propagation speed is one of the important parameters of the internal solitary waves(ISWs). How to obtain the ISWs speed through optical remote sensing images accurately and quickly is an important problem to be solved. In this paper, we simulate ISWs optical remote sensing imaging and obtain an experimental database and build the ISWs speed inversion models based on a single-scene optical remote sensing image by using the least squares method and the support vector machine. The accuracy of the ISW speed inversion models were tested by using MODIS Image and GF-4 image data of the South China Sea. The study results show that: The least squares ISW speed inversion model can give the regression equation, which is more intuitive and has less accuracy in the water depth range from 300 meters to 399 meters, while the support vector machine ISW speed inversion model has high accuracy in the water depth range from 400 meters to 1200 meters and from 83 meters to 299 meters. Therefore, the two kinds of ISW speed inversion models have different advantages, and can be applied to the inversion of the ISW speed in the real ocean.\",\"PeriodicalId\":6995,\"journal\":{\"name\":\"物理学报\",\"volume\":\"99 1\",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"物理学报\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.7498/aps.72.20221633\",\"RegionNum\":4,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"物理学报","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.7498/aps.72.20221633","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
Research on inversion models of internal solitary wave propagation speed in ocean based on least square method and support vector machine
The propagation speed is one of the important parameters of the internal solitary waves(ISWs). How to obtain the ISWs speed through optical remote sensing images accurately and quickly is an important problem to be solved. In this paper, we simulate ISWs optical remote sensing imaging and obtain an experimental database and build the ISWs speed inversion models based on a single-scene optical remote sensing image by using the least squares method and the support vector machine. The accuracy of the ISW speed inversion models were tested by using MODIS Image and GF-4 image data of the South China Sea. The study results show that: The least squares ISW speed inversion model can give the regression equation, which is more intuitive and has less accuracy in the water depth range from 300 meters to 399 meters, while the support vector machine ISW speed inversion model has high accuracy in the water depth range from 400 meters to 1200 meters and from 83 meters to 299 meters. Therefore, the two kinds of ISW speed inversion models have different advantages, and can be applied to the inversion of the ISW speed in the real ocean.
期刊介绍:
Acta Physica Sinica (Acta Phys. Sin.) is supervised by Chinese Academy of Sciences and sponsored by Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences. Published by Chinese Physical Society and launched in 1933, it is a semimonthly journal with about 40 articles per issue.
It publishes original and top quality research papers, rapid communications and reviews in all branches of physics in Chinese. Acta Phys. Sin. enjoys high reputation among Chinese physics journals and plays a key role in bridging China and rest of the world in physics research. Specific areas of interest include: Condensed matter and materials physics; Atomic, molecular, and optical physics; Statistical, nonlinear, and soft matter physics; Plasma physics; Interdisciplinary physics.